How will U.S. stocks perform versus foreign equity markets?

Reader's Question: Do you think the U.S. stock market will provide at least 10% to 20% returns over the next one to two years? Also, how about foreign equity markets?

I am bullish on equities over the long term and think it very possible that the U.S. stock market will see returns around the level you indicate. Negative factors--softness in residential real estate, sub-prime debt problems, possibility of recession, record high oil prices, weakening dollar--have potential to derail the current bull market and will continue to worry investors. Nevertheless, despite the short-term negatives, equity markets tend to exhibit a secular rise on the back of economic growth--and this long-term trend, with solid footing in our world's market economy and capitalism, is unlikely to subside anytime soon.

Think Global

Rather than focussing solely on U.S. equities, I would encourage you to think and invest globally, if you aren't already doing so. The pie chart below shows how the U.S. accounts for about 27% of the world's economy as measured by nominal GDP. This means that almost three-quarters of the world's economic output (i.e., the overwhelming majority of the pie) is generated outside of the U.S. Certainly, the U.S. remains the world's largest economy by a wide margin; however, rapid economic growth rates elsewhere provide a reason to look beyond U.S. borders.



Economic Growth Matters

The world's three largest economies--U.S., Japan and Germany--all have real GDP growth rates in the neighborhood of 2% to 3% annually. That's very sluggish when compared to high growth rates in many other countries among the world's largest 15 economies. Most notably, China continues to show robust 10% to 11% growth, India around 9% or 10%, Russia around 7%, and South Korea and Mexico about 4% to 5% growth. Since GDP growth in the underlying economy drives corporate revenue and earnings growth, which in turn determines stock price performance, it behooves us to focus in on high-growth countries.

As investors, we want growth, but we also want to make sure that we are not paying too much for the growth we get. A good way to gauge the cheapness or richness of entire stock markets is to look at the P/E ratios of representative ETFs. Barclays iShares manages country-specific ETFs that can serve as proxies for most of the largest economies. For example, one of their most popular ETFs is the FTSE/Xinhua China 25 Index (NYSE: FXI), which invests in H-shares of 25 large companies listed in Hong Kong and doing business in China. This China ETF has a market capitalizaion-weighted P/E ratio of 31, as of the end of September.

It is helpful to plot P/E ratio against GDP growth to develop an intuitive feel for how cheap or expensive the various stock markets are. In the graph below, I have drawn lines sloping upward from the origin for the four countries with the most attractive (i.e., lowest) ratios of P/E (for proxy ETFs) to GDP growth rate (for the corresponding countries). This composite ratio is a type of "PEG ratio" that measures P/E relative to growth, allowing for a quick comparison of low-P/E, low-growth and high-P/E, high-growth investment alternatives.



Observe how the ETFs of India (NYSE: INP) and China (NYSE: FXI) offer the most attractive PEG ratios, indicating that even though their respective stock markets are currently trading at relatively high P/Es of 23 (estimated) and 31, respectively, the double-digit (or near-double-digit) growth of their underlying economies appears to support their high-P/E valuations. The ETFs of Mexico (NYSE: EWW) and South Korea (NYSE: EWY) also show attractive PEG ratios.



Prospects for Growth and Profit

Although it is extremely difficult to predict which stock markets will rise the most over the next year or two, or whether the recent strength of global equity markets (particularly China and India) will continue in the near-term, I offer two suggestions:

1. Invest Globally: As a baseline when investing in equities, weight countries in approximate proportion to their contribution to world GDP. ETFs provide a means for taking on exposure to foreign equities while keeping costs and management fees low. Buying ADRs (U.S.-listed shares of foreign companies) is another way to go for those who enjoy (as I do) investing in individual companies. While U.S. equities may comprise the largest single-country contribution, all of the non-U.S. countries together should, in my opinion, add up to more than half of your overall portfolio.

2. Over-weight High-Growth Countries: Given their high GDP growth, China, India, Russia, South Korea and Mexico are good places to search for equity investments. Investors willing to take a long-term view and ride out the higher volatility of these markets stand to benefit from the tailwind that higher GDP growth provides.

Reporting this week of Mukesh Ambani and Carlos Slim's rapid ascent to the #1 and #2 positions in world wealth ranking (both appear to have edged out Bill Gates) is a sign of India and Mexico's strong economic growth and soaring stock market fortunes (as well as evidence of how concentrated wealth is among the super-rich in these countries of relatively low per-capita GDP). Also, Warren Buffett's investment in POSCO (NYSE: PKX) and other South Korean stocks is indicative of the potential upside this Asian market offers.

(Disclosure: The author does not currently have positions in any of the ETFs or stocks mentioned in this article but is overweight in non-U.S. equities from high-growth countries.)

How will U.S. stocks perform versus foreign equity markets?

Reader's Question: Do you think the U.S. stock market will provide at least 10% to 20% returns over the next one to two years? Also, how about foreign equity markets?

I am bullish on equities over the long term and think it very possible that the U.S. stock market will see returns around the level you indicate. Negative factors--softness in residential real estate, sub-prime debt problems, possibility of recession, record high oil prices, weakening dollar--have potential to derail the current bull market and will continue to worry investors. Nevertheless, despite the short-term negatives, equity markets tend to exhibit a secular rise on the back of economic growth--and this long-term trend, with solid footing in our world's market economy and capitalism, is unlikely to subside anytime soon.

Think Global

Rather than focussing solely on U.S. equities, I would encourage you to think and invest globally, if you aren't already doing so. The pie chart below shows how the U.S. accounts for about 27% of the world's economy as measured by nominal GDP. This means that almost three-quarters of the world's economic output (i.e., the overwhelming majority of the pie) is generated outside of the U.S. Certainly, the U.S. remains the world's largest economy by a wide margin; however, rapid economic growth rates elsewhere provide a reason to look beyond U.S. borders.



Economic Growth Matters

The world's three largest economies--U.S., Japan and Germany--all have real GDP growth rates in the neighborhood of 2% to 3% annually. That's very sluggish when compared to high growth rates in many other countries among the world's largest 15 economies. Most notably, China continues to show robust 10% to 11% growth, India around 9% or 10%, Russia around 7%, and South Korea and Mexico about 4% to 5% growth. Since GDP growth in the underlying economy drives corporate revenue and earnings growth, which in turn determines stock price performance, it behooves us to focus in on high-growth countries.

As investors, we want growth, but we also want to make sure that we are not paying too much for the growth we get. A good way to gauge the cheapness or richness of entire stock markets is to look at the P/E ratios of representative ETFs. Barclays iShares manages country-specific ETFs that can serve as proxies for most of the largest economies. For example, one of their most popular ETFs is the FTSE/Xinhua China 25 Index (NYSE: FXI), which invests in H-shares of 25 large companies listed in Hong Kong and doing business in China. This China ETF has a market capitalizaion-weighted P/E ratio of 31, as of the end of September.

It is helpful to plot P/E ratio against GDP growth to develop an intuitive feel for how cheap or expensive the various stock markets are. In the graph below, I have drawn lines sloping upward from the origin for the four countries with the most attractive (i.e., lowest) ratios of P/E (for proxy ETFs) to GDP growth rate (for the corresponding countries). This composite ratio is a type of "PEG ratio" that measures P/E relative to growth, allowing for a quick comparison of low-P/E, low-growth and high-P/E, high-growth investment alternatives.



Observe how the ETFs of India (NYSE: INP) and China (NYSE: FXI) offer the most attractive PEG ratios, indicating that even though their respective stock markets are currently trading at relatively high P/Es of 23 (estimated) and 31, respectively, the double-digit (or near-double-digit) growth of their underlying economies appears to support their high-P/E valuations. The ETFs of Mexico (NYSE: EWW) and South Korea (NYSE: EWY) also show attractive PEG ratios.



Prospects for Growth and Profit

Although it is extremely difficult to predict which stock markets will rise the most over the next year or two, or whether the recent strength of global equity markets (particularly China and India) will continue in the near-term, I offer two suggestions:

1. Invest Globally: As a baseline when investing in equities, weight countries in approximate proportion to their contribution to world GDP. ETFs provide a means for taking on exposure to foreign equities while keeping costs and management fees low. Buying ADRs (U.S.-listed shares of foreign companies) is another way to go for those who enjoy (as I do) investing in individual companies. While U.S. equities may comprise the largest single-country contribution, all of the non-U.S. countries together should, in my opinion, add up to more than half of your overall portfolio.

2. Over-weight High-Growth Countries: Given their high GDP growth, China, India, Russia, South Korea and Mexico are good places to search for equity investments. Investors willing to take a long-term view and ride out the higher volatility of these markets stand to benefit from the tailwind that higher GDP growth provides.

Reporting this week of Mukesh Ambani and Carlos Slim's rapid ascent to the #1 and #2 positions in world wealth ranking (both appear to have edged out Bill Gates) is a sign of India and Mexico's strong economic growth and soaring stock market fortunes (as well as evidence of how concentrated wealth is among the super-rich in these countries of relatively low per-capita GDP). Also, Warren Buffett's investment in POSCO (NYSE: PKX) and other South Korean stocks is indicative of the potential upside this Asian market offers.

(Disclosure: The author does not currently have positions in any of the ETFs or stocks mentioned in this article but is overweight in non-U.S. equities from high-growth countries.)

Airbus A380 - the complete guide and review

For Stephen Bleach, being a part of the inaugural A380 flight on Thursday was revolutionary... but not for all the right reasons

I’ve always been pretty middle of the road, politically speaking. But whenever Gordon Brown deigns to call the next election, I’m voting Socialist Worker’s Party. Eight hours on a plane has turned me into a Marxist.

Not just any plane. I’ve just stepped off the first commercial flight of the A380 superjumbo, the largest passenger aircraft ever built. Yes, it’s impressive: taller than five double-decker buses, wider than a football pitch, 37 times the length of Peter Crouch in his socks, that sort of thing. And yes, it’s an amazing piece of engineering, a staggering technical achievement: but it’s also the best advert for Bolshevism since the tsar said, “Stuff that Lenin chap, let’s build another palace.”

Never has the gap between the haves and the have-nots of the air been more evident. At the front of the plane (business is on the top level, the “super-first” Suites at the front of main deck, economy at the back on both levels), the elite have unparalleled luxury and space. Further back, the proletariat have to... well, let’s not get ahead of ourselves. I’ve just spent eight hours in the cheap seats: here’s a blow-by-blow account.

Takeoff: it just shouldn’t. It doesn’t seem credible that something this size should get into the air at all. Our takeoff weight today was 468 tonnes, which is the equivalent of 12 very surprised sperm whales. And when it finally comes, 50 minutes after we started boarding today’s 455 passengers (they’ll need to speed that up a touch), takeoff is a revelation.

Where other planes crank up the engines to a mighty howl and go for a death-or-glory charge to get airborne, the A380 feels more like an inter-city train leaving a station: silent, gentle, almost imperceptible. There’s a moment of anxiety when the lack of any roar, or bumping, makes you think something is terribly wrong. Then finally, after 40 seconds of smooth, quiet acceleration, this unlikely behemoth leaves the ground with a whisper and drifts quietly into the skies as if it were the most natural thing in the world. After a moment’s collective sigh, everyone breaks into applause. Taking to the air with the A380 does, genuinely, feel like a miracle.

One hour in: as well as kind, civilised folk who’ve bid in a charity auction to be on the first A380 flight, the plane is full of rude, selfish, jostling journalists like me, and the moment the seat-belt sign is turned off, it’s the cue for all of us to leap to our feet and interview mercilessly anyone within notebook distance. We do tend to make a bit of noise, but I didn’t realise we’d actually drown out the engines. That’s how quiet this plane is. In the momentary lulls between hacks barking questions, you can hear the gentle conversations of real people four rows back.

Two hours in: journalistic frenzy over, time for lunch. It’s terrific, produced by a couple of celebrity chefs I’ve never heard of, but will look out for in future. Sam Leong’s fillet of bass with fungi is the best economy-class food I’ve ever had on an airline.

Three hours in: distractions done with, there’s time to take in the surroundings. And when I do, a question occurs. If this is really the most luxurious plane ever built, why am I still shoehorned into a 32in seat?

Here, I have a confession to make. Last week, when the press were first allowed to see the inside of this plane at the Airbus factory, I – along with every journalist there – got a bit overexcited about the double beds in first and the huge business-class seats; all newer, bigger and swisher than anything we’d seen before. As a result, we didn’t spend too much time in the ominously familiar-looking economy area. A sin of omission, for which the hour of judgment has just come. Or rather hours: I’ve got five more to go.

Some passengers say the economy area is much lighter and airier than we’re used to. I don’t see it – though the large windows do provide a better view. The seat is pretty comfortable... for cattle class. My knees don’t touch the seat in front, and it’s an inch or so wider than a standard 747 equivalent. But it’s still not the ideal place to spend eight hours or more of your life, especially when you know that the real high rollers are just a few feet away, in the Suites. Time to see how the other half live...

Four hours in: the airline people are standing close guard on the curtain that separates economy from first, but for an instant they take their eyes off it, and bingo: an advance party of journalists plunges through the gap.

It’s another world. Hushed, spacious, all the seats are in cabins a little like those you’d find on a cruise ship, although the partitions only reach to about eye level. The champagne flows incessantly, and there are normally unobtainable bottles of Château Cos d’Estournel 1982 being poured. In a few of the 12 elite suites, the inhabitants have had their flat beds made up, and sprawl languorously under Givenchy duvets in front of their 23in TVs. Nobody sleeps, though. Having paid up to £25,000 at auction for a ticket, they want to savour every minute.

Upstairs, the improvement in business class, with its colossal 34in-wide seats, is arguably even greater. With just four abreast as opposed to economy’s 10, it feels both communal and spacious. The lucky ones try hard not to look smug. I try hard not to be jealous. We all fail. Five hours in: back in the cheap seats, I ruminate on what might have been. When we were shown the first A380 back in 2003, we were promised the following: boutiques, self-service restaurants, duty-free shops, children’s play areas, casinos, pubs, libraries, gyms (with treadmills to prevent DVT), showers, 18-hole golf courses. (Okay, I made the last one up, but it was going that way.) So why am I sitting here, unexercised, unshowered and unshopped, with the nearest pub in the outback five miles down? Why do we only have a slightly better version of what every long-haul holidaymaker knows and loathes – rank upon rank of sardine-tin seats, with no room to circulate or socialise? Only one conclusion: they were having us on.

Aviation enthusiasts make up the bulk of the clientele today, and they’re determined to enjoy themselves, so I’m in a disgruntled minority (see below). And, to be fair to Singapore Airlines, they never made any of those extravagant claims anyway. But right now I don’t want to be fair. This feels like a missed opportunity.

Six hours in: the real test of a long-haul seat is: Can you sleep in it? I try for 40 winks. Not a chance. The buzz all around means it’s not a fair trial, but I suspect that even on a calmer flight, it wouldn’t be easy. One bonus point: that dried-out, sinusy feeling is noticeably absent. Higher pressurisation is apparently the reason. Seven hours in: time to test the much-vaunted entertainment system. In a stab at egalitarianism, everybody gets the same stuff (economy has a smaller screen, but it’s still a healthy 10+ inches). It’s cracking: 100 on-demand films, 150 TV programmes, 700 CDs. New films, too. There are USB ports and laptop power to every seat. No internet access, though it might come.

Eight hours in: we’re preparing to land, so I’ll sum up. If you’re planning a trip down under when the plane starts flying from London next spring, should you choose an A380? Yes. It’s fabulous in first and business, a touch more comfy than we’re used to at the back. Revolutionary? No – not for the huddled masses, anyway. Vive la révolution. Business class

Business class

Andy Odgers, 39, and Hazel Watt, 43, bagged seats together in business class. Here they are sitting in just one of them. “It’s fantastic, far better than any business class I’ve seen in a 747,” said Andy, “right down to the picture quality on the big TV screen.” The couple, from Richmond in Surrey, paid US$14,200 (£6,922) for the trip, but reckoned it was worth it. “My parents are in Sydney,” said Andy, “and they don’t know anything about us being on this flight. We’re just going to walk into their hotel and surprise them. They’ll be so jealous.” “It’s better than a lot of first-class seats,” said Hazel. “You could argue it’s a bit hot, but it’s the best flight I’ve ever had.”

First class

Julian Hayward, 38, paid top dollar for two seats on the inaugural A380 flight – literally: the one-way trip in the first-class Singapore Suites for himself and a friend set Julian back US$100,380 (£48,936). The entrepreneur invited The Sunday Times in for a cosy chat in his bijou suite. Was it worth it? “Absolutely – all the money goes to charity, so it’s ending up in the right place. And this flight really is a piece of history, the first outing for the biggest plane ever built.” Would he do it again? “Perhaps not for quite so much money! But yes, the standard is something you won’t find elsewhere. I’m very impressed by their wine list. Would you care for a glass?”

Economy class

Richard Killip, 45, bought three tickets for the economy cabin of the A380, and brought along his daughters, Sophie, 12, and Ellie, 10. All three – who hail from Liverpool, but now live in Singapore – loved the flight. “The most impressive thing was the takeoff,” said Richard. “It was so quiet, it was almost spooky.” “I’ve already shown off a little to my schoolfriends,” admits Sophie. “They’re all dead jealous that I’m on the first flight!” Who else will fly the A380?

- PLENTY MORE airlines are queuing up to get the biggest passenger plane on earth. But will they go where you want to fly? When will they start? And – crucially – what will the experience be like on board? Anxious to keep a commercial advantage, most are being cagey with the details. But here’s what we know so far...

QANTAS

Start date: August 2008

Routes: “The US and the UK,” says the airline – which is expected to mean Sydney to London (via Singapore or Hong Kong), plus direct flights from Australia to Los Angeles.

What’s on board?Suites in first class, though not as enclosed as Singapore’s cabins, and no double beds as yet. Lounge with sofas in business. Four self-service bars in economy, and seats by Recaro (which makes seats for Aston Martin). Plus internet access for all.

EMIRATES

Start date:August 2008

Routes:Dubai-London looks certain. Dubai to New York, Australia and India also likely.

What’s on board?Top secret, but there are clues. The airline is installing first-class suites with doors on its fleet of 777s, with styling based on the Orient-Express train, and is expected to go even more luxurious with its A380s – president Tim Clark said: “You ain’t seen nothing yet.” But on flights to India, Emirates will cram in 644 passengers.

AIR FRANCE

Start date:spring 2009

Routes:Paris to New York and Japan.

What’s on board?Questions bring nothing more than a Gallic shrug.

LUFTHANSA

Start date:summer 2009

Routes:20 being considered, from Frankfurt to Asia and North America.

What’s on board?A complete redesign for all three areas, but no details as yet.

BRITISH AIRWAYS

Start date:2012

Routes:Los Angeles, Singapore, Hong Kong and Johannesburg are likely to be first. New York “would be considered if customer demand were strong enough”.

What’s on board?BA only ordered the planes a month ago, so they haven’t decided yet. Don’t expect many gimmicks, though – for that, look to...

VIRGIN ATLANTIC

Start date:2013

Routes:Los Angeles, Dubai.

What’s on board?More double beds for sure, plus a casino – chairman Richard Branson says: “There’ll be two ways to get lucky on our A380s.”

Showers and gyms have been mentioned too.

Four Problem Traders; Four Trading Strengths

A while back I posted on the topic of trader strengths, and readers offered worthwhile perspectives on some of the factors that distinguish successful from unsuccessful traders. After much consideration, I decided to approach the topic a bit differently: by outlining four kinds of problem traders I frequently encounter and by identifying the strengths that help people deal with these problems.

Problem Trader #1: The Frustrated Trader - The frustrated trader deals with frequent angry reactions during trading. Sometimes the anger may be vented outward; other times it is turned inward. For example, many rigidly perfectionistic traders are also frustrated traders, because they cannot live up to their impossible standards and thus artificially create failure experiences for themselves. Frustrated traders are often impulsive traders and will make trades to either compensate for prior losing trades or to make up for missed opportunities. Frustrated traders will often ignore position-sizing rules and undergo occasional blowup losses as a result. It's easy to identify the frustrated trader by their physical cues: yelling, cursing, complaining, and gesturing when they should be focused on the screen. The key strength that combats frustration: self-acceptance and being supportive of oneself. Key techniques for combating frustration: setting reasonable goals; using biofeedback for building self-control and calm focus; and mentally rehearsing trading plans/rules to make them more automatic during the trading day.

Problem Trader #2: The Anxious Trader - The anxious trader is consumed with fears of loss, missing out on objective opportunity either by not taking signals or by sizing positions too conservatively. In a sense, the anxious trader is more concerned about not losing than about winning. This risk aversion can lead to analysis paralysis, as the trader waits for the perfect setup that never quite materializes. Sometimes the anxious trader is one who has been traumatized by prior losses. It's too painful to relive memories of those losses, and so the anxious trader exits positions too quickly and is too reluctant to get into positions. A very common feature is cutting profits rapidly out of fear of losing those. Signs of the anxious trader include muscle tension, worry, relief over getting out of positions (or away from the screen), and inability to trade reasonable size. The key strength that combats anxiety is confidence and an ability to accept loss as a natural part of trading. The techniques most helpful in combating anxiety include cognitive methods for replacing worry talk with constructive problem solving; behavioral techniques to calm oneself and reprogram stress responses; setting process rather than outcome goals; and regaining confidence by trading successfully in simulation mode and gradually building one's size.

Problem Trader #3: The Overconfident Trader - Overconfident traders approach trading like a casino--and they're not the house! The overconfident trader typically overtrades, which means trading size too large for their account and trading more often than opportunity dictates. Very often the overconfident trader is attracted to action in markets, rather than consistent profits and sound discipline. As a result, the overconfident trader can be identified by winning periods punctuated by unusually large and damaging losses. Sometimes the overconfident trader is also a desperate trader, hoping to strike it rich. A common feature of overconfident traders is their lack of preparation: they think that anyone can make it with simple methods and a gut feel. The problem is that they never spend enough time reviewing markets and intensively watching screens to develop that feel. The key strength that combats overconfidence is humility, a respect for markets and risk, and conscientiousness in crafting and following trading rules. Techniques that combat overconfidence include mental rehearsal and self-hypnosis to instill trading rules and support rule-governance; mechanical position sizing to avoid risk of ruin; and cognitive techniques to intercept and challenge grandiose thoughts following winning periods.

Problem Trader #4: The Defeated Trader - Defeated traders are ones who, in trader parlance, have "lost their mojo". Their thought patterns are negative and this blinds them to opportunity. Very often they will be filled with shame, remorse, and guilt over past losses and very often they enter new trades expecting the worst. As a result, they don't often enter new trades and will miss out on opportunities that are genuinely present. They often stop working at their trading, as anything trading-related is associated with emotional pain. Defeatism thus becomes a self-fulfilling prophecy. It's easy to recognize defeated traders, not only by their depressed mood, low energy, and lack of enthusiasm, but also by their "yes, but" rejection at helping efforts. Very often the defeated trader will focus on losses and mistakes and gloss over progress that's been made: they see the trading cup as half empty, rather than half full. The key strength that combats defeatism is emotional resilience and the ability to use losses as learning experiences. Techniques that combat defeatism include cognitive methods for reprocessing negative thought patterns; structuring of the learning process to emphasize strengths and solutions rather than mistakes; and a focus on attainable goals and the creation of success experiences.

Most of us can identify elements of these four traders in ourselves. If I had to choose, I'd say that I am most like the Anxious Trader. I am quick to step away from markets when my setups aren't there--sometimes too quick! Many of the traders I work with fit into the Frustrated Trader category: they're aggressive, achievement-oriented, and hard on themselves.

Knowing your patterns does not, in itself, enable you to change them, but it's a necessary step. Indeed, I find that, regardless of the patterns, the first step of progress a trader makes is interrupting old patterns that aren't working and trying something different. The ability to stand outside oneself as an observer of patterns is a core self-coaching skill.

Can sentiment predict market direction?

Question: Is investor sentiment a useful indicator of market direction? If possible, I would like to trade on sentiment to make money.

Blogger Sentiment

Popular measures of investor sentment are reported in Barron's each week. For brief background reading, try the Investopedia article entitled "Investors Intelligence Sentiment Index." The article cites an academic study published in 2000 by Ken Fisher and Meir Statman that concluded: "We found the relationship between the sentiment of newsletter writers as measured by the Investors Intelligence survey and future S&P 500 returns to be negative but not statistically significant." As is the case with most (if not all?) fundamental and technical indicators, the prospect of using a simple sentiment index to trade and consistently realize excess profits does not look very encouraging.

However, instead of giving up so easily, let's have a look at a newer sentiment index that is being tracked by Ticker Sense, a financial blog of Birinyi Associates, run by former Salomon executive Laszlo Birinyi. Beginning in July of 2006, Ticker Sense has been reporting at the start of each trading week market sentiment figures resulting from a poll sent out to participating bloggers the prior Thursday. Bloggers state whether they are bullish, bearish or neutral on the S&P 500 for the upcoming 30 days. The chart below shows this sentiment data for the past 12 months.



We can develop a qualitative feel for how useful this type of sentiment data might be in a trading context by plotting the S&P 500 index alongside the weekly difference between the bull and bear sentiment percentages. The chart below shows that for the past couple of months blogger sentiment has correlated favorably with the directional movement of the S&P 500 index--the market moves down with negative bull-bear sentiment in early August, up with positive bull-bear sentiment from about mid-August through the market's recent highs in early October, and down on slightly negative sentiment last week. Hey, this is beginning to look promising. . . .



"Batting Average" Test

One barometer for gauging how helpful blogger sentiment can be in predicting market direction is to perform a "batting average" calculation. A baseball player's batting average is a number between zero and 1.000 (or zero and 1000, if we ignore the decimal point), indicating the ratio of hits to at-bats during a season. For example, during 2004 when Seattle Mariners all-star player Ichiro set a new all-time major league baseball record with 262 hits, his batting average in his 704 season at-bats was 262/704 = 0.372.

In an analogous fashion, we can define a sentiment "batting average" as being the time-average of the relevant (bull, bear or neutral) sentiment percentages corresponding to the actual up, down and flat market outcomes observed during all of the trials in a specified testing period:

Sentiment "Batting Average" = Sum(X_i)/N,

where

X_i = bullish (bearish, neutral) sentiment percentage at time i-1 if market return ends up in bullish (bearish, neutral) range at time i,

and i runs from 1 to N, inclusive, where N is the number of trials in the testing period.

(Note: Since the Ticker Sense sentiment poll is updated at a weekly frequency, for our analysis we pair each week's sentiment data with only the following week's market movement. In effect, sentiment predictions are "refreshed" each week, even though bloggers participating in the poll are asked for their opinion about the next 30 days.)

Here's a numerical example: If a particular week's sentiment poll gives bull-bear-neutral sentiment percentages of 50-30-20 and the market ends up falling into the bearish range the week after the poll is taken, this particular trial contributes an X-value of 0.300 to the average. Obviously, the highest batting average is attained when the actual market movement always matches the strongest prevailing sentiment (or highest percentage) among the three possible sentiment "states" (bull, bear and neutral).

Two extreme cases help to clarify the meaning of our sentiment "batting average": If all bloggers participating in the poll had complete clairvoyance, the sentiment percentages would always be 100-0-0 (bullish), 0-100-0 (bearish) or 0-0-100 (neutral), and each trial would always contribute an X-value of 1.000, resulting in a perfect time-average of 1.000. At the other extreme, if the bloggers were always completely split without any predominating opinion, the sentiment percentages would be 33-33-33 (rounded), and each trial would always contribute an X-value of 0.333, regardless of whether the market rises, falls or remains flat. Importantly, this batting average of 0.333 is also the expected outcome when collective opinion, whether skewed or split, is no better than a random guess at determining market direction.

In order to apply our batting-average methodology to the blogger sentiment data, we also need to define what we mean by bullish, bearish and neutral outcomes, and ideally these three "states" should be equally likely, so that no particular outcome is favored over the others. To take into account the possibility of "trending" regimes, rather than referencing static return ranges I use a 26-week moving window ending just prior to each weekly trial:

"Bullish": Above 67th percentile return of immediately prior 26 weeks

"Neutral": Between 33rd and 67th percentile return of immediately prior 26 weeks

"Bearish": Below 33rd percentile return of immediately prior 26 weeks

Though there is some variation from week to week, for the S&P 500 over the past year the 26-week moving averages of the 33rd and 67th percentile weekly returns have hovered around -0.3% and 1.2%, respectively, giving sentiment ranges approximately as follows:

"Bullish": Weekly return above 1.2%

"Neutral": Weekly return between -0.3% and 1.2%

"Bearish": Weekly return below -0.3%

The graph below shows the week-by-week contributions to the overall average. For example, for the week ending October 5, bullish sentiment (from the poll sent out Thursday of the prior week) was 50% and the market traded up, thereby contributing an X-value of 0.500. Note, however, that the overall average from the past one year is the smaller figure of 0.319, which is slightly worse than the 0.333 expected in the case of random guessing. In other words, the batting-average calculation suggests that blogger sentiment will probably not be very useful in predicting market direction.



Simulated Trading Test

Another way to visualize the sentiment data is to look at scatterplots of the bull-bear sentiment difference (at time i-1) versus S&P 500 returns for the following week (at time i). I divide the past year into two 26-week periods to enable us to run two simulated trading tests on the sentiment data.

For the first 26-week period, from October 2006 through April 2007, there is a somewhat negative correlation between sentiment and returns, suggesting that sentiment could be slightly contra-indicative of market direction.



However, over the next 26-week period, from April 2007 through October 2007, the correlation is essentially zero, indicating no apparent relationship between sentiment and subsequent returns.



We can trade on the sentiment data by using the weekly bull-bear sentiment differences to weight one-week trades on the S&P 500 index (or futures), going long when the difference is positive (net bullish) and going short when it is negative (net bearish). Trade size equals the absolute value of the bull-bear sentiment difference, so that we take larger trading positions when sentiment is more extremely bullish or bearish. The graph below shows the simulated outcome of such trading over our two 26-week periods. The initial 26-week trading period produces a loss, while the later 26-week trading period begins in negative territory but goes slightly positive from early August to early October when sentiment, as mentioned above, matches market direction.



Is There Hope?

Overall, with the batting-average test failing to show all-star-like performance above the 0.333 expected value of random guessing, and the trading test producing what appears to be little more than a random walk, it is difficult to place any confidence in blogger sentiment as a useful predictor of market direction.

But, perhaps we should not overlook how traders, investors and bloggers (myself included) all learn as we go, thereby opening up the possibility that the blogger sentiment index could be an example of a self-improving dynamic system engaged in an adaptive learning process. The most recent two months certainly show promise, and sentiment data from last Thursday's poll (bull-bear-neutral: 50-33-17), with bloggers turning bullish following last week's 4% sell-off, again matches the S&P 500's interim performance so far this week (up from Friday's 1501 close)--though, of course, it is too early to tell how the remainder of the week will turn out.

What, then, should we believe: the negative overall read from the past year, or the more promising performance of sentiment over the past few months? Rather than allowing our hopes to rise too high, I suggest keeping in mind a market truism: if there really is any predictive power in a well-publicized indicator, opportunistic traders will soon exploit this information, thereby squelching any excess returns that might have been available. Maybe, then, the trick is to be quick--exploit the winning "streak" before it vanishes! Good luck trading!

Can sentiment predict market direction?

Question: Is investor sentiment a useful indicator of market direction? If possible, I would like to trade on sentiment to make money.

Blogger Sentiment

Popular measures of investor sentment are reported in Barron's each week. For brief background reading, try the Investopedia article entitled "Investors Intelligence Sentiment Index." The article cites an academic study published in 2000 by Ken Fisher and Meir Statman that concluded: "We found the relationship between the sentiment of newsletter writers as measured by the Investors Intelligence survey and future S&P 500 returns to be negative but not statistically significant." As is the case with most (if not all?) fundamental and technical indicators, the prospect of using a simple sentiment index to trade and consistently realize excess profits does not look very encouraging.

However, instead of giving up so easily, let's have a look at a newer sentiment index that is being tracked by Ticker Sense, a financial blog of Birinyi Associates, run by former Salomon executive Laszlo Birinyi. Beginning in July of 2006, Ticker Sense has been reporting at the start of each trading week market sentiment figures resulting from a poll sent out to participating bloggers the prior Thursday. Bloggers state whether they are bullish, bearish or neutral on the S&P 500 for the upcoming 30 days. The chart below shows this sentiment data for the past 12 months.



We can develop a qualitative feel for how useful this type of sentiment data might be in a trading context by plotting the S&P 500 index alongside the weekly difference between the bull and bear sentiment percentages. The chart below shows that for the past couple of months blogger sentiment has correlated favorably with the directional movement of the S&P 500 index--the market moves down with negative bull-bear sentiment in early August, up with positive bull-bear sentiment from about mid-August through the market's recent highs in early October, and down on slightly negative sentiment last week. Hey, this is beginning to look promising. . . .



"Batting Average" Test

One barometer for gauging how helpful blogger sentiment can be in predicting market direction is to perform a "batting average" calculation. A baseball player's batting average is a number between zero and 1.000 (or zero and 1000, if we ignore the decimal point), indicating the ratio of hits to at-bats during a season. For example, during 2004 when Seattle Mariners all-star player Ichiro set a new all-time major league baseball record with 262 hits, his batting average in his 704 season at-bats was 262/704 = 0.372.

In an analogous fashion, we can define a sentiment "batting average" as being the time-average of the relevant (bull, bear or neutral) sentiment percentages corresponding to the actual up, down and flat market outcomes observed during all of the trials in a specified testing period:

Sentiment "Batting Average" = Sum(X_i)/N,

where

X_i = bullish (bearish, neutral) sentiment percentage at time i-1 if market return ends up in bullish (bearish, neutral) range at time i,

and i runs from 1 to N, inclusive, where N is the number of trials in the testing period.

(Note: Since the Ticker Sense sentiment poll is updated at a weekly frequency, for our analysis we pair each week's sentiment data with only the following week's market movement. In effect, sentiment predictions are "refreshed" each week, even though bloggers participating in the poll are asked for their opinion about the next 30 days.)

Here's a numerical example: If a particular week's sentiment poll gives bull-bear-neutral sentiment percentages of 50-30-20 and the market ends up falling into the bearish range the week after the poll is taken, this particular trial contributes an X-value of 0.300 to the average. Obviously, the highest batting average is attained when the actual market movement always matches the strongest prevailing sentiment (or highest percentage) among the three possible sentiment "states" (bull, bear and neutral).

Two extreme cases help to clarify the meaning of our sentiment "batting average": If all bloggers participating in the poll had complete clairvoyance, the sentiment percentages would always be 100-0-0 (bullish), 0-100-0 (bearish) or 0-0-100 (neutral), and each trial would always contribute an X-value of 1.000, resulting in a perfect time-average of 1.000. At the other extreme, if the bloggers were always completely split without any predominating opinion, the sentiment percentages would be 33-33-33 (rounded), and each trial would always contribute an X-value of 0.333, regardless of whether the market rises, falls or remains flat. Importantly, this batting average of 0.333 is also the expected outcome when collective opinion, whether skewed or split, is no better than a random guess at determining market direction.

In order to apply our batting-average methodology to the blogger sentiment data, we also need to define what we mean by bullish, bearish and neutral outcomes, and ideally these three "states" should be equally likely, so that no particular outcome is favored over the others. To take into account the possibility of "trending" regimes, rather than referencing static return ranges I use a 26-week moving window ending just prior to each weekly trial:

"Bullish": Above 67th percentile return of immediately prior 26 weeks

"Neutral": Between 33rd and 67th percentile return of immediately prior 26 weeks

"Bearish": Below 33rd percentile return of immediately prior 26 weeks

Though there is some variation from week to week, for the S&P 500 over the past year the 26-week moving averages of the 33rd and 67th percentile weekly returns have hovered around -0.3% and 1.2%, respectively, giving sentiment ranges approximately as follows:

"Bullish": Weekly return above 1.2%

"Neutral": Weekly return between -0.3% and 1.2%

"Bearish": Weekly return below -0.3%

The graph below shows the week-by-week contributions to the overall average. For example, for the week ending October 5, bullish sentiment (from the poll sent out Thursday of the prior week) was 50% and the market traded up, thereby contributing an X-value of 0.500. Note, however, that the overall average from the past one year is the smaller figure of 0.319, which is slightly worse than the 0.333 expected in the case of random guessing. In other words, the batting-average calculation suggests that blogger sentiment will probably not be very useful in predicting market direction.



Simulated Trading Test

Another way to visualize the sentiment data is to look at scatterplots of the bull-bear sentiment difference (at time i-1) versus S&P 500 returns for the following week (at time i). I divide the past year into two 26-week periods to enable us to run two simulated trading tests on the sentiment data.

For the first 26-week period, from October 2006 through April 2007, there is a somewhat negative correlation between sentiment and returns, suggesting that sentiment could be slightly contra-indicative of market direction.



However, over the next 26-week period, from April 2007 through October 2007, the correlation is essentially zero, indicating no apparent relationship between sentiment and subsequent returns.



We can trade on the sentiment data by using the weekly bull-bear sentiment differences to weight one-week trades on the S&P 500 index (or futures), going long when the difference is positive (net bullish) and going short when it is negative (net bearish). Trade size equals the absolute value of the bull-bear sentiment difference, so that we take larger trading positions when sentiment is more extremely bullish or bearish. The graph below shows the simulated outcome of such trading over our two 26-week periods. The initial 26-week trading period produces a loss, while the later 26-week trading period begins in negative territory but goes slightly positive from early August to early October when sentiment, as mentioned above, matches market direction.



Is There Hope?

Overall, with the batting-average test failing to show all-star-like performance above the 0.333 expected value of random guessing, and the trading test producing what appears to be little more than a random walk, it is difficult to place any confidence in blogger sentiment as a useful predictor of market direction.

But, perhaps we should not overlook how traders, investors and bloggers (myself included) all learn as we go, thereby opening up the possibility that the blogger sentiment index could be an example of a self-improving dynamic system engaged in an adaptive learning process. The most recent two months certainly show promise, and sentiment data from last Thursday's poll (bull-bear-neutral: 50-33-17), with bloggers turning bullish following last week's 4% sell-off, again matches the S&P 500's interim performance so far this week (up from Friday's 1501 close)--though, of course, it is too early to tell how the remainder of the week will turn out.

What, then, should we believe: the negative overall read from the past year, or the more promising performance of sentiment over the past few months? Rather than allowing our hopes to rise too high, I suggest keeping in mind a market truism: if there really is any predictive power in a well-publicized indicator, opportunistic traders will soon exploit this information, thereby squelching any excess returns that might have been available. Maybe, then, the trick is to be quick--exploit the winning "streak" before it vanishes! Good luck trading!

How 9 Internet Startups Lost 2 Billion Dollars

To an outsider looking in, venture capitalists may look like the cavalry of the gravy train. Images come to mind of handsome men in sharp looking suits, swooping in on helicopters with briefcases full of money for people like us to follow our dreams. But to the insider who has actually worked in those fields, venture capitalists are just that. Capitalists. They are businessmen whose jobs, just like any other businessman, are to make money. And like anyone else, they are capable of mistakes. Aggressive lending and bad management can easily destroy any business. And no where is this more famous than in the tech industry.

Webvan -- Webvan started as a reasonably sensible idea, "A Super Market that Delivers!" Unfortunately the leeway offered through $800,000,000 gave the company enough slack to hang itself with its own spending. With those kinds of funds at Webvan's disposal the company grew at such a rate that it overextended itself. Throughout a period of eighteen months, Webvan expanded its reach from San Francisco to eight other cities across the United States. At its zenith it reached a value of over 1.2 billion dollars. But supermarkets already have razor-thin profit margins. Add that with the burden of a new, untested business model, and the growing pains alone were enough to finish off the company. To this day, one may be able to find WebVan logos in the nooks and hideaways of AT&T park (then Pacific Bell), the stadium Webvan sponsored when it thought it had money to throw away.

Pets.com -- Started by Greg McLemore then bought by venture cap firm Hummer Winblad and executive Julie Wainwright, Pets.com was proof that it takes more than a "money is no object" marketing campaign to save you. The talking sock-puppet Pets.com became known for was a balloon in the Macy's Thanksgiving Day Parade and even made it into the crown jewel of all television advertising, a spot during the Super Bowl. But as popular as their mascot was, Pets.com was never able to convince its prospective customers why they should buy their pet supplies online. Ironically, it could be said that the initial investors were directly to blame for Pets.com's downfall. Investors pumped millions into the company with the predetermined knowledge that it would be thrown at marketing. Then, before any real value had been established within the company itself, Pets.com was made public. The company still could have plausibly been saved, but the investors instead allowed it to die quickly without giving it any long-term opportunity to grow. With the release of its IPO, Pets.com raised $82.5 million only to disappear less than a year later.

Kozmo.com -- A great idea poorly executed. Kozmo.com was founded by investment bankers Joseph Park and Yong Kang. The company's purpose was simple: to deliver a wide variety of small goods within an hour for no delivery charge. Wanted popcorn, soda, and a movie on your doorstep in under an hour? No problem! Unfortunately for Kozmo, the gimmick that made it famous, "Free Delivery", was also its undoing. The company claimed that the money saved by not needing rental space for store fronts would easily offset the costs of delivery. This however was not the case as the company would shut its doors after only three years of service. Kozmo raised roughly $250 million in funding including $60 million directly from Amazon.com, but one wonders what their logic was when they promised $150 million of that money to Starbucks for advertising.

Flooz.com -- Why spend dollars when you can use the internet's own new currency, "Flooz!" Why indeed? Flooz.com would go belly-up after only two and half years, but not before burning through something between $35 and $50 million in venture capital funding. With that kind of money it's obvious how Flooz.com was able to afford their spokesperson, Oscar-winner Whoopi Goldberg. Despite acquiring a well-received spokesperson, one has to question the rest of this company's logic. Namely, why would someone exchange currency backed by the United States government for currency backed by only a fledgling internet startup company in New York? At least gift cards are backed by their merchant. When Flooz.com went under, all Flooz credit became worthless.

eToys.com -- At first glance eToys.com seemed like a sound idea, "Sell toys on the internet!" However, when placed in the context of competing with an alliance between Amazon.com and Toys 'R' Us, it's obvious how bleak the picture really was. Funded by "idealab!" eToys raised $166 million with its IPO, but within 16 months its share price went from a high of $84 down to a low of 9 cents. "Idealab!" itself would be burned so badly through its tech investments that it would close a number of its offices and cancel its own IPO. Like other internet startups, eToys would burn through the bulk of its income through aggressive marketing and expensive advertisements. In the end however, its income would never exceed its spending. The company went under in less than two years after its IPO.

Go.com -- As a web portal, Go.com became definitive proof that even the "old guard" weren't safe from blowing large amounts of money by investing in the tech industry. Created by the Walt Disney Internet Group, Go.com was founded in 1995, but really began in 1998 when it merged with Infoseek. The intention was for Go.com to become a destination site, much like Yahoo, or later Google. Countless millions were spent in advertising with the site never growing popular enough to justify the costs. In the end, many people lost their jobs and Disney took a write off of $790 million. A lot of cash, even for a company like Disney. Go.com exists today but uses Yahoo as its search engine and only carries feeds from other Disney Web properties.

Boo.com -- As Go.com proved that even the "old guard" weren't safe, Boo.com showed that losing huge amounts of money through investing in the tech industry wasn't something bound solely within the United States. Based in the United Kingdom, Boo.com was an online store that specialized in brand name clothing. Setting aside "keeping it simple" the executives instead prioritized giving their web pages a sexy design steeped heavily in JavaScript and Flash technology. From a virtual sales assistant to web pages that took several minutes to load, Boo.com was a website that did not keep the customers first in mind. Its one saving grace, "free returns" where Boo.com would pay the postage for all returns, was not logistical for a company serving an international community. After two years, Boo.com folded having burned through $160 million.

GovWorks.com -- Founded by childhood friends Kaleil Tuzman and Tom Herman, GovWorks.com began as a way for people to pay their parking tickets online. But with Kaleil serving as salesman and Tom designing the technology, GovWorks.com grew into a site with the intention of allowing people to perform all necessary business with municipal governments online. Kaleil and Tom quickly found themselves hobnobbing with power players within the United States government, and were able to gather $60 million in venture capital funds. Soon afterwards however, tension grew between the two friends, and Tom was kicked out of the company. In the end, GovWorks.com was a complete flop and was taken over by a competitor.

MVP.com -- Your online sports equipment store! With John Elway as chairman, and Michael Jordan and Wayne Gretzky serving as directors, MVP.com was the veritable Planet Hollywood of the internet. But like Planet Hollywood, it took more than big names to keep the company afloat. It also took more than the mere $65 million war chest MVP.com started with. After entering into a four-year advertising deal with CBS, MVP.com promptly failed to pay the $10 million a year it had agreed to within their contract. All this despite the fact that MVP.com charged the same amount online as one would find in a retail store. The company folded soon after and was taken over by CBS's online affiliate Sportsline.com.

When companies such as these fail, it is more than just a website going down. Consumers are left with fewer choices, and today's new online companies find it that much more difficult to raise capital. Ideas that could bring fabulous new services to the marketplace will never see the light of day due to the careless failures of their predecessors. Unfortunately, the same thing is still going on today. EONS, the social network for senior citizens has had $32 million invested into it despite sporting such tasteful features as an obituary section. Although not a website, Amp'd Mobile recently went under, burning through $360 million in only two years. Often, ill-fated business decisions can be attributed to naivety, but other times it is plainly more malicious. Filmloop.com recently went under, because its primary funding venture capital firm forced it to sell for bottom dollar, despite the business doing well. In other cases, venture capital groups have made countless new companies possible through initial funding, only to then dog-ear that money for marketing to produce buzz. Once that buzz was established and the stock had raised, the venture capitalists would sell and move on, leaving the public share holders to bear the collapse of a company that could have made it had it been given a chance through patience, and better management. In this list alone, almost $2.5 billion was lost. Money that could have been better spent than in the risky world of venture capital.

SAP: SAP Should Follow Oracle’s Lead

There has been plenty of hot air expelled this week over whether SAP’s (SAP - Annual Report) acquisition of Business Objects (BOBJ) is a sign that it is adopting Oracle’s (ORCL - Annual Report) big acquisition strategy or whether it is a simply a larger part of SAP’s existing strategy of using small “tuck-in” acquisitions. I’ll leave others to bloviate on those issues.

I am less interested in whether SAP is following Oracle’s strategy than whether they ought to be. And I think the answer to that question is a resounding “yes.”

For one thing, corporate IT buyers’ main concerns tend to be reducing costs and reducing complexity. Much better to have Oracle and SAP tie together the applications from a number of vendors (by directly integrating them) than to devote in-house IT staff to doing it. Research 2.0 criticizes the Business Objects acquisition for this reason, saying “SAP now faces many of the same incompatible architectural challenges faced by Oracle with its many acquisitions.” I think their customers would rather have SAP deal with the incompatibilities than to have to do it themselves. Since when is making life easier for customers a bad thing?

More importantly, however, there are just too darn many application software manufacturers out there. While consolidation in some industries occurs because the weaker businesses fail, software balance sheets are generally too strong to for this to happen. The only way to fix the problem of too many customers chasing a relatively fixed amount of dollars is for an industry leader to soak up the excess capital by leveraging its own balance sheet to acquire other companies - for cash, not shares. Oracle has been pursuing that fix.

Software companies tend to generate significant cash flow, and Oracle has been able to use this cash flow to fund the acquisitions while both maintaining a healthy balance sheet and avoiding dilution to existing shareholders. As an example, consider its first large acquisition – that of PeopleSoft in January 2005 for $11.1 billion in cash. Prior to the acquisition Oracle held more than $9.5 billion in cash and marketable securities on its balance sheet, and had virtually no debt. The company used this cash and a $7 billion bridge loan to complete the acquisition, and by the end of its fiscal year in May, 2005 it had reduced the loan value to $2.6 billion while still maintaining nearly $5 billion in cash and marketable securities and actually reducing its share count.

By May, 2006 the company had made another $4 billion worth of acquisitions (net of the cash held by the acquired companies) and increased its cash and marketable securities to $7.5 billion while restructuring its debt load to $5.7 billion in long-term debt. Even though the debt was $3 billion more than the prior year, most of that was offset by the increase in cash – meaning that the $4 billion in acquisitions was made possible almost entirely through cash flow from operations.

Speaking of cash flow, in the year ended May 2007 Oracle generated $5.5 billion of it from operating activities, and spent only $320 million of it on capital expenditures. That turns out to be a free cash flow yield of 4.5% from the existing businesses. Most of that continues to be invested in new acquisitions for new growth opportunities. The free cash flow has increased 55% since FY2005.

Meanwhile, SAP is generated approximately $2.0 billion in free cash flow last year, giving it a 3.0% free cash flow yield. Its acquisition avoidance has left the free cash flow essentially unchanged over the last three years (though arguably the change in the Euro/dollar exchange rate is providing growth.)

A higher yield and growing free cash flow compared with a lower, flat one is not much of a choice in my book.

If any doubt remains over which strategy is working better, one need only turn to a price chart. Since Oracle closed the PeopleSoft acquisition in January 2005, its shares are up 70% (mostly driven by rising cash flow), compared to just more than 30% for SAP over the same time. To me, it seems like that is exactly the type of “challenge” SAP would want to adopt.

How can I use the PEG ratio to value stocks?

Reader's Question: I have a started to pay attention to PEG ratios. Can you please explain how to calculate the PEG ratio for a stock? Can you show how Apple's (Nasdaq: AAPL) PEG is 1.6, as you indicated in an earlier post? How can PEG be used to value stocks? What is a good source for finding estimated five-year growth rates?

Calculation of PEG

The PEG ratio is a straightforward way to combine two fundamental aspects of stock analysis for the purpose of gauging how cheap or rich a stock is trading:

Earnings: Traditional value-oriented analysis looks at price ratios, the most common of which is the price-to-earnings, P/E, or "PE ratio." At a given level of earnings (E), a lower price (P) results in a lower PE ratio, providing investors with a "cheaper" investment.

Growth: Extension of PE ratio analysis to include growth can be accomplished by simply dividing the PE ratio by the earnings growth rate (G), which gives (P/E)/(100 x G), or the "PEG ratio." The factor of 100 is included to convert the growth rate from a percentage to a number of percentage points (e.g., 15% = 0.15, becomes 0.15 x 100 = 15). Since PE ratios are typically around 15 to 20, and growth rates are often in the 10% to 15% range, the PEG ratio is often numerically around 1 or 2 (note that the S&P 500 has a PEG ratio of 1.64, according to data from the Yahoo! Finance Stock Screener). As with PE ratio, a lower PEG ratio generally indicates a "cheaper" stock.

To run through an example for Apple (Nasdaq: AAPL): In the earlier post that you refer to, from back in early September, when Apple was priced at $144 per share, the trailing 12 months (July 2006 to June 2007) of reported earnings were $3.55, the one-year forward (to Sep-2008) consensus earnings estimate was about $4.40, and the consensus earnings growth estimate for the upcoming five years was 22.5%. At that time, I calculated the PEG ratio for Apple as follows:

PEG = {$144/[($3.55 + $4.40)/2]}/(100 x 0.225) = 1.6 (as of close on 04-Sep-2007),

where I use the average of the trailing 12 months (ttm) and one-year forward earnings to generate a proxy for "current" earnings on an annualized basis.

Today, with Apple trading 21% higher at $174 per share and the one-year forward consensus earnings estimate having been raised to $4.58 through revisions reported by the 27 analysts covering the company, the PEG ratio calculates to:

PEG = {$174/[($3.55 + $4.58)/2]}/(100 x 0.225) = 1.9 (as of close on 18-Oct-2007).

The higher PEG, caused by the rise in the stock price, reflects Apple's richer valuation, versus a month and a half ago. Surely, we would be measurably wealthier today if we had bought Apple in early September at $144 (corresponding to the lower PEG of 1.6) and held our shares through today's close of $174 (corresponding to the higher PEG of 1.9).

PEG and Returns

Now, if succeeding at investing were as simple as buying low-PE or low-PEG stocks and selling out at higher PE and PEG ratios, it would seemingly be easy to make money. Generally, what we, as investors, really want to do is maximize our return-on-investment. In other words, while PE and PEG are convenient price ratios that help to describe a stock, ultimately we are more concerned with the compounded annual return, R, in the formula:

(Price at 5-Year Horizon) = (Price Today) x (1 + R)⁵,

where we select a five-year investment horizon to match up with the standard five-year term used in earnings growth estimates provided by Wall Street analysts.

It is instructive to understand how PE, growth rate and PEG all relate to return-on-investment. By definition of the PE ratio (i.e., PE = P/E), we can write:

(Price at 5-Year Horizon) = PE₅ x E₅ = PE₅ x E₀ x (1 + G)⁵,

applying, in the second equality, the definition of earnings growth from today to the end of year five. Setting the right-hand sides of the above equations equal to one another and rearranging, we can write:

(1 + R)⁵ = (PE₅/PE₀) x (1 + G)⁵,

recognizing that (Price Today)/E₀ = P₀/E₀ = PE₀.

Although analysts report estimated five-year earnings growth rates (G), the terminal PE ratio at the end of the five-year investment horizon (PE₅) is not a commonly reported figure. Since the purpose of this discussion is to look at five-year returns, I am going to assume for the scope of our calculations that the terminal PE ratio equals the analyst consensus five-year earnings growth rate (multitplied by a factor of 100). To see why this is a reasonable assumption to make, let's again look at numbers for Apple: since G = 22.5%, we are assuming that PE₅ = 100 x G = 22.5. Today, Apple's PE ratio based on current earnings is about 43. We are essentially assuming that over the next five years, as the company's iPod and iPhone product lines mature and both revenue and earnings growth decelerate, Apple's relatively high current PE ratio of 43 will fall to a terminal five-year value of 22.5, which is about half of where it is today.

Our terminal PE assmption allows us to rewrite our return equation as:

(1 + R)⁵ = (100 x G/PE₀) x (1 + G)⁵ = (1/PEG) x (1 + G)⁵,

which tells us that return, R, is high when the PEG ratio is low and the earnings growth rate (G) is high. In other words, in order to maximize our investment return, we are concerned not only with low PEG--we will also want to pay close attention to companies that have high earnings growth rates.

While our last result is conceptually appealing, it turns out that PE and PEG ratios are more readily available in online databases than the growth rate, G. Consequently, for convenience we use the definition of PEG to rewrite the return equation as:

(1 + R)⁵ = (1/PEG) x [1 + PE₀/(100 x PEG)]⁵,

or, solving explicitly for the return-on-investment:

R = [1 + PE₀/(100 x PEG)]/PEG^0.2 - 1.

To help visualize what this equation means, I provide the graph below, showing contours of constant PE. Observe that calculated returns are higher for lower values of PEG. Also, for a given level of PEG, a higher PE ratio (implicitly indicating a higher earnings growth rate) produces higher returns.



We can also take a look at contours of constant return, as indicated in the plot of PEG ratio versus current PE ratio below.



Back to our example for Apple: If we had bought the stock in early September at $144, when the current PE ratio was 36 and the PEG was 1.6, our pro forma five-year annualized return would be 11.4%. The same calculation today with Apple's share price at $174, current PE ratio of 43, and PEG ratio of 1.9 gives a pro forma return of 7.7%. Since the stock price has risen 21%, while our assumptions about future earnings growth remain unchanged, anyone buying the stock today should, of course, reasonably expect to earn a lower return, compared to having bought Apple shares when they were cheaper in early September.

Application to Dow Component Stocks

To build our intuition about the relationship of return to PE and PEG ratios, it is helpful to look at actual market data for familiar stocks, such as the 30 components of the Dow Jones Industrial Average. The scatterplot below shows the PE and PEG ratios for each of the Dow 30 component stocks. JP Morgan Chase (NYSE: JPM) has the lowest PE ratio, at 9.5, while McDonald's (NYSE: MCD) has the highest PE ratio, at 25.6. AIG (NYSE: AIG) has the lowest PEG ratio, at 0.78, while Pfizer (NYSE: PFE) has the highest PEG ratio, at 2.74.



Using our expression for return, R, we can proceed to calculate the pro forma five-year returns based on the PE and PEG data, again assuming that the terminal PE at the five-year horizon equals the five-year earnings growth rate as projected by the analyst consensus estimate. Results are plotted below.



Notice that there is a very strong correlation between low PEG and high pro forma return. AIG, trading at a low PEG of 0.78 (PE = 9.9, G = 12.7%) produces the highest pro forma return, a very respectable annualized rate of 18%. At the other end of the spectrum is Pfizer, with a PEG of 2.74 (PE = 10.3, G = 3.8%) that leads to a strongly negative pro forma return of -15%. It is the measly estimated growth rate of 3.8%, coupled with the assumption that the terminal PE equals this growth rate (indeed, a PE ratio of 3.8 is awfully low!) that produces the substantial loss on a pro forma basis.



Cautionary Remarks

As with most (maybe even all) analytical frameworks for valuing stocks, the formulation presented above has its shortcomings. The pro forma returns are calculated by relying on two key underlying assumptions to make the otherwise formidable problem tractable:

Consensus Earnings Growth Estimates: Analysts periodically revise their earnings and earnings growth estimates, based on new information about a company's business plans, the competitive landscape, industry pressures, and the overall economic outlook. Five-year growth estimates, though the "best available" at any point in time, can and do vary considerably from quarter to quarter and year to year.

Terminal PE Ratio: While our assumption that the terminal PE ratio at the five-year horizon equals the five-year earnings growth rate may be a reasonable one that allows for a "ballpark" comparison of pro forma returns for investment in many different stocks across diverse industries, it simply is not possible to determine PE ratios so far forward in time with any degree of confidence and accurary.

Consequently, we cannot and should not expect the calculated pro forma returns to end up closely predicting the actual returns that will materialize over the next five years. The financial world is complex and continually changing and, with this change, our assumptions themselves need to shift as the months and years go by. Think of stock forecasting models as being like "the man who is always 100% confident, except that his opinion changes from day to day." You see, on any particular day it is possible to peer five years into the future; but you must realize too that our predictions today about future years will generally be very different from our predictions next month about these same future years.

Nevertheless, the PE and PEG ratios, while having limited predictive power, do remain useful tools for assessing the cheapness or richness of stocks--at least in the current market environment, and at least relative to other stocks in the same or similar industries. For an analysis of potential returns offered by leading U.S. and Chinese Internet stocks, applying techniques explained in this article, please see my recent post highlighting prospects for Baidu (Nasdaq: BIDU) and Google (Nasdaq: GOOG).

Data Source

A comprehensive source for stock data is Yahoo! Finance. The Key Statistics page for any listed stock includes the trailing 12-month PE, forward 1-year PE, and PEG ratio. From these PE and PEG ratios, we can obtain the five-year earnings growth rate, G, by working through the definition, PEG = (P/E)/(100 x G). The consensus five-year earnings growth estimates, G, are given on the Analyst Estimates page for any listed stock, along with PE and PEG ratios.

(Disclosure: Among the stocks mentioned in this article, the author holds or manages long positions in Baidu and Google.)